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Record W4392949231 · doi:10.32920/25418179.v1

Mind Your Speech: Examining the Impact of Leader Mindfulness in Communication on Follower Error Reporting and Hiding in Organizations

2024· preprint· en· W4392949231 on OpenAlexaff
Fallan Mitchell

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicOrganizational Learning and Leadership
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMindfulnessPsychologyCognitive psychologySocial psychologyApplied psychologyComputer scienceLinguisticsPsychotherapistPhilosophy

Abstract

fetched live from OpenAlex

<p>Although researchers have demonstrated an increasing interest in the interpersonal antecedents of error reporting in employees, little is known about how interpersonal-level factors influence employee error hiding. Using a three-wave time-lagged survey design (N = 186), the present study investigates whether leader mindfulness in communication, a communication style exhibited by mindful leaders, predicts follower error hiding and reporting through two distinct mediators-- fear of punishment and relatedness, respectively. Findings reveal that leader mindfulness in communication negatively predicts follower error hiding, mediated by fear of punishment, and positively predicts follower error reporting through the organization's error management culture rather than via feelings of relatedness. It was further discovered that relatedness predicts error reporting, but not hiding. Similarly, fear of punishment predicts error hiding, but not reporting. This paper contributes to our understanding of the interpersonal antecedents and distinct motives behind error reporting and hiding while advancing research on mindfulness at work.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score0.790

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.115
GPT teacher head0.331
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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